scholarly journals Classification of Chronic Obstructive Pulmonary Disease (COPD) Using Regression with Gabor Filtration and Random Forest Classification

Author(s):  
Porkod V ◽  
2017 ◽  
Vol 25 (3) ◽  
pp. 811-827 ◽  
Author(s):  
Dimitris Spathis ◽  
Panayiotis Vlamos

This study examines the clinical decision support systems in healthcare, in particular about the prevention, diagnosis and treatment of respiratory diseases, such as Asthma and chronic obstructive pulmonary disease. The empirical pulmonology study of a representative sample (n = 132) attempts to identify the major factors that contribute to the diagnosis of these diseases. Machine learning results show that in chronic obstructive pulmonary disease’s case, Random Forest classifier outperforms other techniques with 97.7 per cent precision, while the most prominent attributes for diagnosis are smoking, forced expiratory volume 1, age and forced vital capacity. In asthma’s case, the best precision, 80.3 per cent, is achieved again with the Random Forest classifier, while the most prominent attribute is MEF2575.


2020 ◽  
Vol 14 (3) ◽  
pp. 155798832092263
Author(s):  
Ichraf Anane ◽  
Fatma Guezguez ◽  
Hend Knaz ◽  
Helmi Ben Saad

No study has evaluated the utility of different classifications of chronic obstructive pulmonary disease (COPD) airflow limitation (AFL) in terms of the refined “ABCD” classification of the Global Initiative for Chronic Obstructive Lung Disease (GOLD) or in terms of the impacts on quality of life. This study aimed to compare some relevant health outcomes (i.e., GOLD classification and quality-of-life scores) between COPD patients having “light” and “severe” AFL according to five COPD AFL classifications. It was a cross-sectional prospective study including 55 stable COPD male patients. The COPD assessment test (CAT), the VQ11 quality-of-life questionnaire, a spirometry, and a bronchodilator test were performed. The patients were divided into GOLD “A/B” and “C/D.” The following five classifications of AFL severity, based on different post-bronchodilator forced expiratory volume in 1 s (FEV1) expressions, were applied: FEV1%pred: “light” (≥50), “severe” (<50); FEV1z-score: “light” (≥−3), “severe” (<−3); FEV1/height2: “light” (≥0.40), “severe” (<0.40); FEV1/height3: “light” (≥0.29), “severe” (<0.29); and FEV1Quotient: “light” (≥2.50), “severe” (<2.50). The percentages of the patients with “severe” AFL were significantly influenced by the applied classification of the AFL severity (89.1 [FEV1z-score], 63.6 [FEV1%pred], 41.8 [FEV1/height3], 40.0 [FEV1Quotient], and 25.4 [FEV1/height2]; Cochrane test = 91.49, df = 4). The CAT and VQ11 scores were significantly different between the patients having “light” and “severe” AFL. In GOLD “C/D” patients, only the FEV1Quotient was able to distinguish between the two AFL severities. To conclude, the five classifications of COPD AFL were not similar when compared with regard to some relevant health outcomes.


1994 ◽  
Vol 36 (5) ◽  
pp. 403-408 ◽  
Author(s):  
Jorge O Lopes ◽  
Maria C Bassanesi ◽  
Sydney H Alves ◽  
Adenilde Salla ◽  
Jeni P Benevenga ◽  
...  

This paper reports a case of cutaneous infection of nontraumatic origin caused by Nocardia asteroides in a hospitalized patient with chronic obstructive pulmonary disease. Diagnosis was established by direct and histological examination, cultures from exudate and biopsy specimen. We discuss the classification of clinical forms of Nocardia infections affecting the skin.


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